Jane Street's head of technology just explained the full spectrum of how fast their trading decisions are made.
the fastest systems turn around a packet in under 100 nanoseconds. at that speed, if you attached an oscilloscope to the wire going in and the wire going out, you'd see the response start to leave before the incoming packet has finished arriving.
at that speed, you can't use a CPU. you can't use any programming language. you're on an FPGA direct wired to the network. and the decisions you're making are incredibly simple. because you literally can't compute anything complex in that time.
but here's the part most people miss: that's just one end of the spectrum.
Jane Street runs an ensemble of systems operating at every timescale simultaneously. some decisions happen in nanoseconds. some in microseconds. some in milliseconds. some take hours or a full day.
"the right way to build an optimal trading strategy is an ensemble approach. for some decisions you're making very simple decisions very quickly. for others, you're operating at the scale of microseconds, milliseconds. and in some cases, if you can get that decision turned around in an hour, that's totally fine."
the faster you need to respond, the simpler the decision has to be. the slower you can afford to go, the smarter the model can be.
this is why "Jane Street is just a speed game" is wrong. speed is one dimension. intelligence is the other.
Your brain has a circuit that doesn't know you live in a city. Its only job is to monitor whether birds are still singing. Right now, in this room, it is on.
The circuit predates primates. Mammals have been using ambient soundscape continuity as a predator-detection system for roughly 200 million years. Birds stop singing when something larger moves through their territory. For most of mammalian history, a forest full of song meant no large predator was nearby, and the cessation of sound was the warning. Your nervous system never updated this software.
The Max Planck Institute tested the inverse in 2022 with 295 participants. Six minutes of birdsong dropped anxiety with a medium effect size. Six minutes of traffic noise raised depression with the same. The effect worked on subjects who lived in dense urban environments and had no regular contact with nature. The brain still ran the check.
Birdsong sits in the 1,000 to 8,000 Hz range. Your brainstem reads continuous patterns in that band as a signal that nothing dangerous is currently moving through the environment. EEG data shows birdsong at 45 to 50 decibels boosts alpha wave activity by 14.1% relative to silence. Alpha is the brainwave signature of relaxed alertness. Push the same birdsong above 60 decibels and the response flips. Stress markers rise 29%. The circuit only trusts the signal at the volume of quiet conversation, which is exactly the volume birds sing at from a typical distance.
Three things happen simultaneously when the brain registers ambient safety. The amygdala downregulates. The parasympathetic nervous system takes over from the sympathetic. Heart rate variability rises, cortisol drops. The posterior cingulate cortex, which sits at the center of the rumination circuit, quiets down. King's College London tracked this through a smartphone study with over 1,200 participants and found the mood lift lasted hours after the sound stopped. People diagnosed with depression got the same response as healthy controls.
Most of what gets labeled mental fatigue is hypervigilance running in the background. Birdsong tells the circuit it can stand down, and the brain reallocates the freed compute everywhere else.
A quiet park feels different from a quiet office because the parks have sentinels.
holy fuck, a hair dryer at a Paris airport broke Polymarket weather markets & made someone $34,000 richer
- polymarket was settling Paris temperature bets on a single Météo France sensor sitting near the Charles de Gaulle runway perimeter - basically unguarded
- the guy bought the long-shot outcome (like "22°C" when everyone expected 18°C) for pennies, since nobody thought it'd hit
- then he walked up to the probe and briefly heated the air around it with a portable heat source, spiking the reading just long enough to register as the daily max
- temperature snapped back to normal in minutes, the market resolved in his favor, and he cashed out - twice, on April 6 and April 15, before Météo France caught on and filed charges
hyperstitions.
> be Adobe, 40-year-old PDF jockey
> 2025, stock doing a perfect -33% swan dive
> “We’ll pivot to AI” says exec on 7-figure retention bonus
> can’t ship a model because legal says every pixel needs a 12-page EULA
> Midjourney drops v7, makes our Firefly look like MS Paint with a hangover
> OpenAI drops GPT-Image, Google drops nano-banana, both free
> our response: “Please login with your Adobe ID, install Creative Cloud, update 47 GB, restart, then pay $53.99/month”
> users collectively Alt-F4 into orbit
> watch in horror as ChatGPT/Gemini reads any PDF you give it for free
> enterprise cancels 10k seats overnight
> try to counter with Sora killer video model
> training cluster catches fire after someone uploads a 1998 clipart library
> PR tweet: “We are re-imagining creativity”
> quote-tweet ratio hits 1:9k, gif of dumpster bonfire tops replies
> premiere pro is now just a bloated launcher for 15 different subscription prompts
> 20-something with a phone and CapCut is making better edits
> our flagship feature: “Generative fill but now 3% slower”
> board meeting: “Let’s raise prices again”
> stock drops another 8% during the Zoom call
> our most innovative feature in 5 years is a "subscribe to annual plan" button that clicks itself
Ever notice stuff like
“Why are broke guys so good in bed?” or “Why are the hottest people so boring?”
It feels like there’s a tradeoff between traits, but that’s often an illusion.
What’s really happening is this -- when you filter for people who score high on the sum of two traits (e.g. total dating appeal), you start to see a negative correlation between those traits within that group, even if no such tradeoff exists in the broader population.
It’s a statistical artifact. You’re looking at people who made the cut overall.
The plot attached shows it --
Looks and coolness are uncorrelated in the population, but once we filter for people with high "total attractiveness" (looks + coolness), a negative correlation emerges.
This doesn’t just apply to dating, it shows up anytime you’re selecting based on the total of two uncorrelated or loosely related traits.
>Women create site to dox men with half truths and gossip
>Instead end up getting doxxed themselves, with government issued IDs confirming their identity, paired with plaintext leaks showcasing toxic behavior, with non-repudiation
and that's the tea, sis